Heterogeneity, immunological mechanisms and translational prospects of tertiary lymphoid structures in cancer therapy

Junjie Zheng; Hui Huang; Wanqiao Li; Shijia Li; Jialin Liu; Zhihao Lu; Cihui Yan; Wencheng Zhang

doi:10.59717/j.xinn-oncol.2026.100011

The Innovation Oncology > 2026 Vol. 1 > No. 1 > 100011

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Heterogeneity, immunological mechanisms and translational prospects of tertiary lymphoid structures in cancer therapy

1.
Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
2.
Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Gastrointestinal Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China
3.
Department of Immunology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Immunology and Biotherapy, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China

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Corresponding authors: pppeirain@126.com (Z.L.); cihuiyan@tmu.edu.cn (C.Y.); wczhang@tmu.edu.cn (W.Z.)
Received Date: March 03, 2026

Accepted Date: April 23, 2026

Published Online: April 25, 2026

The Innovation Oncology 1(1), https://doi.org/10.59717/j.xinn-oncol.2026.100011 | Cite this article

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GRAPHICAL ABSTRACT

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PUBLIC SUMMARY

PUBLIC SUMMARY
1. Tertiary lymphoid structures are organized immune niches that can shape cancer therapy outcomes.
  
  Their impact depends on maturation, location, and effector-versus-suppressive immune balance.
  
  Chemotherapy, radiotherapy, and immunotherapy can remodel tertiary lymphoid structures over time.
  
  Standardized tertiary lymphoid structure assessment may improve biomarkers and combination therapy.

ABSTRACT

ABSTRACT

Tumor-associated tertiary lymphoid structures (TA-TLS) represent ectopic lymphoid neogenesis within chronically inflamed tumors and are increasingly linked to response to immune checkpoint blockade (ICB) and other anticancer therapies. However, TLS are not uniformly beneficial: their immune outputs vary with maturation, spatial niche (intratumoral, invasive margin, or peritumoral), and the balance between effector programs and suppressive modules. This heterogeneity, together with inconsistent definitions and measurement approaches, has limited cross-cohort comparability and slowed translation of TLS into reliable biomarkers and therapeutic targets. In this review, we synthesize key pathways governing TLS induction, formation, and maturation, emphasizing vascular and stromal scaffold requirements that enable lymphocyte recruitment and compartmentalization. We summarize and reconcile existing TLS classification frameworks across tumor types, and integrate mechanistic interactions among T cells, B cells, dendritic cells, myeloid populations, and stromal elements that shape TLS “quality” and immunological function. Importantly, we highlight therapy-induced TLS remodeling as a dynamic process influenced by chemotherapy, radiotherapy dose/fractionation and sequencing, anti-angiogenic strategies, and ICB itself—helping explain divergent clinical associations and suggesting time-ordered opportunities for intervention. Finally, we discuss multimodal approaches for standardized TLS assessment and outline emerging strategies to safely engineer high-quality TLS to enhance antitumor immunity and rationalize combination regimens.
- Tertiary lymphoid structures /
- Tumor microenvironment /
- TLS induction /
- Heterogeneity /
- Cancer Therapy

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Zheng J., Huang H., Li W., et al. (2026). Heterogeneity, immunological mechanisms and translational prospects of tertiary lymphoid structures in cancer therapy. The Innovation Oncology 1:100011. https://doi.org/10.59717/j.xinn-oncol.2026.100011

Zheng J., Huang H., Li W., et al. (2026). Heterogeneity, immunological mechanisms and translational prospects of tertiary lymphoid structures in cancer therapy. The Innovation Oncology 1:100011. https://doi.org/10.59717/j.xinn-oncol.2026.100011

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